[Remote/WFM] Product Manager, AI Ecosystems in GKE, Google Cloud

Core Information:

• Start Date: Immediate openings available
• Compensation: a competitive salary
• Company: GKE, Google Cloud
• Location: Remote
• Position: Product Manager, AI Ecosystems

 

 

Minimum qualifications: • Bachelor's degree or equivalent practical experience. • 5 years of experience in product management or related technical role. • 2 years of experience developing or launching products or technologies within artificial intelligence or Machine Learning (AI or ML). Preferred qualifications: • Master's degree in a technology or business related field. • 3 years of experience in a business function or role (e.g., strategic marketing, business operations, consulting). • Knowledge of artificial intelligence, Generative AI workloads, AI training, AI inference, AI infrastructure, MLOps, NVIDIA GPUs, or TPUs. • Ability to work with ambiguity, setting goals and delivering them in a very fast-changing environment. About the job At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day. In this role, you will work cross-functionally... to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development. One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users. Google Kubernetes Engine (GKE) is a scalable and automated Kubernetes service available from any public cloud provider, enabling developers and businesses to run containerized applications on Google Cloud. As organizations everywhere adopt AI, GKE has potential for growth and impact. The GKE AI ecosystem and onboarding team is dedicated to diversifying the GKE AI customer base by reducing the time and effort required for customers to scale their production AI workloads through ensuring GKE supports the broad ecosystem of ML tools, frameworks, and open models. Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. The US base salary range for this full-time position is $142,000-$211,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google . Responsibilities • Work with partner teams (e.g., engineers, program managers, UX) during product design and development to implement the requirements to turn PRDs into OKRs for one or more teams. • Develop and secure buy-in for a product idea that identifies, defines, and supports the overall product narrative and direction. • Ensure the broad ecosystem of ML tools, frameworks, and open models are well supported by and integrated with GKE. • Reduce the time and effort needed for customers to scale their AI workloads from prototype to production. • Improve GKE's integration with Vertex AI to deliver a unified proposition for AI customers Apply Job!

 

We Encourage You to Apply!

Even if you feel you're not a perfect match, we'd still love to hear from you. We are looking for great people to join our friendly team.

apply to this job